GHC provides multi-scale support for parallel and concurrent programming, from very fine-grained, small "sparks", to coarse-grained explicit threads and locks, along with other models of concurrent and parallel programming, including actors, CSP-style concurrency, nested data parallelism and Intel Concurrent Collections. Synchronization between tasks is possible via messages, regular Haskell variables, MVar shared state or transactional memory.

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</p>

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* '''Software Transactional Memory''' (STM) is a new way to coordinate concurrent threads. There's a separate [[Software transactional memory|Wiki page devoted to STM]].

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: STM was added to GHC 6.4, and is described in the paper [http://research.microsoft.com/~simonpj/papers/stm/index.htm Composable memory transactions]. The paper [http://research.microsoft.com/~simonpj/papers/stm/lock-free.htm Lock-free data structures using Software Transactional Memory in Haskell] gives further examples of concurrent programming using STM.

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* '''Foreign function interface'''. If you are calling foreign functions in a concurrent program, you need to know about ''bound threads''. They are described in a Haskell workshop paper, [http://research.microsoft.com/~simonpj/Papers/conc-ffi/index.htm Extending the Haskell Foreign Function Interface with Concurrency]. The GHC Commentary [http://www.cse.unsw.edu.au/~chak/haskell/ghc/comm/rts-libs/multi-thread.html Supporting multi-threaded interoperation] contains more detailed explanation of cooperation between FFI calls and multi-threaded runtime.

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== Getting started ==

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* '''Nested Data Parallelism'''. For an approach to exploiting the implicit parallelism in array programs for multiprocessors, see [[GHC/Data Parallel Haskell|Data Parallel Haskell]] (work in progress).

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The most important (as of 2010) to get to know are the basic "concurrent Haskell" model of threads using forkIO and MVars, the use of transactional memory via STM.

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See "[http://research.microsoft.com/en-us/um/people/simonpj/papers/marktoberdorf/ Tackling the Awkward Squad]" to get started.

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=== Using concurrency in GHC ===

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From there, try the [[Parallel/Reading|reading list for parallelism in Haskell]].

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* You get access to concurrency operations by importing the library [http://www.haskell.org/ghc/docs/latest/html/libraries/base/Control-Concurrent.html Control.Concurrent].

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== Digging deeper ==

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* The GHC manual gives a few useful flags that control scheduling (not usually necessary) [http://www.haskell.org/ghc/docs/latest/html/users_guide/sec-using-parallel.html#parallel-rts-opts RTS options].

: STM was added to GHC 6.4, and is described in the paper [http://research.microsoft.com/~simonpj/papers/stm/index.htm Composable memory transactions]. The paper [http://research.microsoft.com/en-us/um/people/simonpj/papers/stm/#lock-free Lock-free data structures using Software Transactional Memory in Haskell] gives further examples of concurrent programming using STM.

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* '''Foreign function interface'''. If you are calling foreign functions in a concurrent program, you need to know about ''bound threads''. They are described in a Haskell workshop paper, [http://research.microsoft.com/~simonpj/Papers/conc-ffi/index.htm Extending the Haskell Foreign Function Interface with Concurrency]. The GHC Commentary [http://darcs.haskell.org/ghc/docs/comm/rts-libs/multi-thread.html Supporting multi-threaded interoperation] contains more detailed explanation of cooperation between FFI calls and multi-threaded runtime.

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=== Multiprocessor GHC ===

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== GHC concurrency specifics ==

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As of version 6.5, GHC supports running programs in parallel on an SMP or multi-core machine. How to do it:

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You get access to concurrency operations by importing the library [http://www.haskell.org/ghc/docs/latest/html/libraries/base/Control-Concurrent.html Control.Concurrent].

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* You'll need to get a version of GHC that supports SMP. Either download a [http://www.haskell.org/ghc/dist/current/dist nightly snapshot distribution], or [http://hackage.haskell.org/trac/ghc/wiki/GhcDarcs get the sources] from darcs and build it yourself.

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{{GHC/Multicore}}

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* You need to link your program using the <tt>-threaded</tt> switch. (NOTE: previously it was necessary to compile all code, including libraries, with the <tt>-smp</tt> switch, this is no longer the case. The <tt>-smp</tt> flag is now a synonym for <tt>-threaded</tt>).

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Support for low-level parallelism features of modern processors is slowly coming along. As of version 7.8, GHC includes the ability to [https://ghc.haskell.org/trac/ghc/wiki/SIMD emit SIMD instructions], and also has a rudimentary ability to use [[AtomicMemoryOps|atomic memory operations]].

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* Run the program with <tt>+RTS -N2</tt> to use 2 threads, for example. You should use a <tt>-N</tt> value equal to the number of CPU cores on your machine (not including Hyper-threading cores).

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== Alternative approaches ==

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* Concurrent threads (<tt>forkIO</tt> and <tt>forkOS</tt>) will run in parallel, and you can also use the <tt>par</tt> combinator and Strategies from the [http://www.haskell.org/ghc/docs/latest/html/libraries/base/Control-Parallel-Strategies.html Control.Parallel.Strategies] module to create parallelism.

Contents

Overview

GHC provides multi-scale support for parallel and concurrent programming, from very fine-grained, small "sparks", to coarse-grained explicit threads and locks, along with other models of concurrent and parallel programming, including actors, CSP-style concurrency, nested data parallelism and Intel Concurrent Collections. Synchronization between tasks is possible via messages, regular Haskell variables, MVar shared state or transactional memory.

Getting started

The most important (as of 2010) to get to know are the basic "concurrent Haskell" model of threads using forkIO and MVars, the use of transactional memory via STM.

Run the program with +RTS -N2 to use 2 threads, for example (RTS stands for runtime system; see the GHC users' guide). You should use a -N value equal to the number of CPU cores on your machine (not including Hyper-threading cores). As of GHC v6.12, you can leave off the number of cores and all available cores will be used (you still need to pass -N however, like so: +RTS -N).

Concurrent threads (forkIO) will run in parallel, and you can also use the par combinator and Strategies from the Control.Parallel.Strategies module to create parallelism.